Inhaltszusammenfassung

Latent state–trait theory (LSTT) considers the fact that measurement does not take place in a situational vacuum. LSTT decomposes any observed variable into a latent state component and a measurement error component, and any latent state into a latent trait component and a latent state residual representing situational influence and/or interactional influences. Furthermore, it provides more precise reliability estimates than common coefficients. This article introduces the basic concepts of L...Latent state–trait theory (LSTT) considers the fact that measurement does not take place in a situational vacuum. LSTT decomposes any observed variable into a latent state component and a measurement error component, and any latent state into a latent trait component and a latent state residual representing situational influence and/or interactional influences. Furthermore, it provides more precise reliability estimates than common coefficients. This article introduces the basic concepts of LSTT, discusses its usefulness for public opinion research, and applies LST models to panel data on political efficacy from the 2009 German Longitudinal Election Study. The findings show that internal efficacy is a rather trait-like disposition and external efficacy is significantly due to situational and/or interactional influences.» weiterlesen» einklappen

Autoren

Klassifikation

DFG Fachgebiet:
Sozialwissenschaften

DDC Sachgruppe:
Psychologie